Communications of the ACM - Special issue on parallelism
Automatic Creation of Object Hierarchies for Ray Tracing
IEEE Computer Graphics and Applications
Heuristics for ray tracing using space subdivision
The Visual Computer: International Journal of Computer Graphics
Physically Based Rendering: From Theory to Implementation
Physically Based Rendering: From Theory to Implementation
Scan primitives for GPU computing
Proceedings of the 22nd ACM SIGGRAPH/EUROGRAPHICS symposium on Graphics hardware
Scalable Parallel Programming with CUDA
Queue - GPU Computing
Fast scan algorithms on graphics processors
Proceedings of the 22nd annual international conference on Supercomputing
Real-time KD-tree construction on graphics hardware
ACM SIGGRAPH Asia 2008 papers
On fast Construction of SAH-based Bounding Volume Hierarchies
RT '07 Proceedings of the 2007 IEEE Symposium on Interactive Ray Tracing
Understanding the efficiency of ray traversal on GPUs
Proceedings of the Conference on High Performance Graphics 2009
Designing efficient sorting algorithms for manycore GPUs
IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
Parallel SAH k-D tree construction
Proceedings of the Conference on High Performance Graphics
HLBVH: hierarchical LBVH construction for real-time ray tracing of dynamic geometry
Proceedings of the Conference on High Performance Graphics
Memory-Scalable GPU Spatial Hierarchy Construction
IEEE Transactions on Visualization and Computer Graphics
Efficient data management for incoherent ray tracing
Applied Soft Computing
Efficient divide-and-conquer ray tracing using ray sampling
Proceedings of the 5th High-Performance Graphics Conference
Parallel divide and conquer ray tracing
SIGGRAPH Asia 2013 Technical Briefs
Fully parallel kd-tree construction for real-time ray tracing
Proceedings of the 18th meeting of the ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games
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KD-tree is one of the most efficient acceleration data structures for ray tracing. In this paper, we present a kd-tree construction algorithm that is precisely SAH-optimized and runs entirely on GPU. We construct the tree nodes in breadth-first order. In order to precisely evaluate the SAH cost, we design a parallel scheme based on the standard parallel scan primitive to count the triangle numbers for all split candidates, and a bucket-based algorithm to sort the AABBs (axis-aligned bounding box) of the clipped triangles of the child nodes. The proposed parallel algorithms can be mapped well to GPU's streaming architecture. The experiments showed that our algorithm can produce the highest quality kd-tree as the off-line CPU algorithms, but runs faster than multi-core CPU algorithms and the GPU SAH BVH-Tree algorithm.